Back color images supporting "Functional movement screen dataset collected with two Azure Kinect depth sensors"

This is color images of Azure Kinect sensor in back position.

This dataset supports the following publication: Xing, QJ., Shen, YY., Cao, R. et al. Functional movement screen dataset collected with two Azure Kinect depth sensors. Sci Data 9, 104 (2022). https://doi.org/10.1038/s41597-022-01188-7 See related materials in collection at:
https://doi.org/10.25452/figshare.plus.c.5774969
Collection Description:
This presents a dataset for vision-based autonomous functional movement screen (FMS) collected from 45 human subjects of different ages (18-59 years old) executing the following movements: deep squat, hurdle step, in-line lunge, shoulder mobility, active straight raise, trunk stability push-up, and rotary stability. Specifically, shoulder mobility was performed only once by different subjects, while the other movements were repeated for three episodes each. Each episode was saved as one record and was annotated from 0 to 3 by three FMS experts. The main strength of our database is twofold. One is the multimodal data provided, including color images, depth images, and 3D human skeleton joints. The other is the multiview data collected from the two synchronized Azure Kinect sensors in front of and on the side of the subjects. Finally, three-dimensional trajectories, quaternions, and 2D pixel trajectories of 32 joints were recorded. Our dataset contains a total of 1812 recordings, with 3624 episodes. The size of the dataset is 158 GB. As a supplement, we also provide color image data from the other two cameras (back and side low positions). This dataset provides the opportunity for automatic action quality evaluation of FMS.

本数据集展示了Azure Kinect传感器在背位拍摄的颜色图像。该数据集支持以下出版物：Xing, QJ., Shen, YY., Cao, R. 等人. 使用两个Azure Kinect深度传感器收集的功能运动筛查数据集。科学数据 9, 104 (2022)。https://doi.org/10.1038/s41597-022-01188-7 相关材料请参见：https://doi.org/10.25452/figshare.plus.c.5774969

集合描述：本集合提供了一套基于视觉的自主功能运动筛查（FMS）数据集，该数据集从45名不同年龄（18-59岁）的受试者中收集，受试者执行以下动作：深蹲、跨栏步、直线弓箭步、肩关节活动度、主动直臂上举、躯干稳定性俯卧撑和旋转稳定性。具体而言，肩关节活动度由不同受试者各执行一次，而其他动作则每人重复三次。每个动作序列被保存为一个记录，并由三位FMS专家进行0至3的标注。我们数据库的主要优势在于其多模态数据，包括彩色图像、深度图像和3D人体骨骼关节。其次，数据集收集了来自位于受试者前方和侧方的两个同步Azure Kinect传感器的多视角数据。最后，记录了32个关节的三维轨迹、四元数和二维像素轨迹。本数据集包含总共1812个记录，3624个动作序列，数据集大小为158 GB。作为补充，我们还提供了来自其他两个摄像头（背部和侧面低位）的彩色图像数据。该数据集为FMS的自动动作质量评估提供了机会。